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Reverse Nearest Neighbor Query Method and Device Based on Semantic Trajectory Big Data

A technology of trajectory big data and query method, applied in the field of communication, can solve problems such as not being able to meet the realization of RkNNST

Active Publication Date: 2021-07-27
SHIJIAZHUANG TIEDAO UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, in the prior art, spatial indexes for semantic trajectories, such as STR-tree, MV3R-tree, and MTSB-tree, only focus on global spatial features, while spatial text indexes such as IR tree and I3 only consider snapshots of spatial text objects position, which cannot meet the needs of implementing RkNNST on semantic trajectories

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  • Reverse Nearest Neighbor Query Method and Device Based on Semantic Trajectory Big Data
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  • Reverse Nearest Neighbor Query Method and Device Based on Semantic Trajectory Big Data

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Embodiment Construction

[0024] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0025] In order to illustrate the technical solutions of the present invention, specific examples are used below to illustrate.

[0026] refer to figure 1 , figure 1 A schematic diagram of a general example of reverse nearest neighbor query for the semantic track provided by the embodiment of the present invention.

[0027] t1, t2 and t3 are three semantic trajectories. Each location is associ...

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Abstract

The present invention is applicable to the field of communication technology, and provides a reverse nearest neighbor query method and device based on semantic trajectory big data, wherein the method includes: establishing a trajectory index IMC tree according to the trajectory data set, wherein the IMC tree includes inverted list and a plurality of MC trees, the inverted list is used to store the keyword vocabulary, and the MC tree includes a track summary for storing the local position of the track; according to the query data set, the query index WIBR tree is established; through the IMC tree and The WIBR tree performs alternate access to determine the query result rnn of the query q k (q), the query result is the minimum relevant sub-track with the query q as the nearest neighbor query in the IMC tree. The present invention provides a reverse nearest neighbor query method and device based on semantic trajectory big data, which can realize the reverse nearest neighbor query on the semantic trajectory and obtain more specific and accurate query results.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a reverse nearest neighbor query method and device based on semantic trajectory big data. Background technique [0002] With the popularity and application of mobile devices and social networks, a large amount of semantically rich trajectory data (ie, semantic trajectory) is generated. The semantic trajectory includes a series of spatial text points, and each spatial text point includes a spatial position and a set of keywords. The keyword set is the semantic label of the spatial text point. Due to the rich knowledge contained in semantic trajectories, semantic trajectory retrieval has attracted great attention from commercial organizations and research institutions. Existing research on semantic trajectory retrieval mainly focuses on K-nearest neighbor query (kNN, k-NearestNeighbor). Reverse nearest neighbor query, as one of the important query types, has no...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/953G06F16/9536G06F16/31G06F16/33G06Q50/00
CPCG06Q50/01
Inventor 潘晓吴雷
Owner SHIJIAZHUANG TIEDAO UNIV